Pandas Profiling Report

Dataset statistics

Number of variables	14
Number of observations	10682
Missing cells	0
Missing cells (%)	0.0%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	1.1 MiB
Average record size in memory	112.0 B

Variable types

Numeric	10
Categorical	4

Warnings

`year_of_Journey` has constant value "2019"	Constant
`month_of_Journey` is highly correlated with `week_of_Journey`	High correlation
`week_of_Journey` is highly correlated with `month_of_Journey`	High correlation
`Source` is highly correlated with `year_of_Journey`	High correlation
`month_of_Journey` is highly correlated with `year_of_Journey`	High correlation
`year_of_Journey` is highly correlated with `Source` and 2 other fields	High correlation
`Total_Stops` is highly correlated with `year_of_Journey`	High correlation
`df_index` is uniformly distributed	Uniform
`df_index` has unique values	Unique
`Airline` has 319 (3.0%) zeros	Zeros
`Destination` has 2871 (26.9%) zeros	Zeros
`minute_of_Journey` has 2062 (19.3%) zeros	Zeros

Reproduction

Analysis started	2021-08-27 05:35:40.787974
Analysis finished	2021-08-27 05:35:54.717358
Duration	13.93 seconds
Software version	pandas-profiling v2.11.0
Download configuration	config.yaml

df_index
Real number (ℝ_≥0)

UNIFORM
UNIQUE

Distinct	10682
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	5340.65381
Minimum	0
Maximum	10682
Zeros	1
Zeros (%)	< 0.1%
Memory size	83.6 KiB

Quantile statistics

Minimum	0
5-th percentile	534.05
Q1	2670.25
median	5340.5
Q3	8010.75
95-th percentile	10147.95
Maximum	10682
Range	10682
Interquartile range (IQR)	5340.5

Descriptive statistics

Standard deviation	3083.997576
Coefficient of variation (CV)	0.5774569343
Kurtosis	-1.199877355
Mean	5340.65381
Median Absolute Deviation (MAD)	2670.5
Skewness	0.0001753776066
Sum	57048864
Variance	9511041.05
Monotocity	Strictly increasing

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
2047	1	< 0.1%
1346	1	< 0.1%
5440	1	< 0.1%
9534	1	< 0.1%
3387	1	< 0.1%
1338	1	< 0.1%
7481	1	< 0.1%
5432	1	< 0.1%
9526	1	< 0.1%
3379	1	< 0.1%
Other values (10672)	10672	99.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	1	< 0.1%
1	1	< 0.1%
2	1	< 0.1%
3	1	< 0.1%
4	1	< 0.1%

Value	Count	Frequency (%)
10682	1	< 0.1%
10681	1	< 0.1%
10680	1	< 0.1%
10679	1	< 0.1%
10678	1	< 0.1%

Airline
Real number (ℝ_≥0)

ZEROS

Distinct	12
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	3.966204831
Minimum	0
Maximum	11
Zeros	319
Zeros (%)	3.0%
Memory size	83.6 KiB

Quantile statistics

Minimum	0
5-th percentile	1
Q1	3
median	4
Q3	4
95-th percentile	8
Maximum	11
Range	11
Interquartile range (IQR)	1

Descriptive statistics

Standard deviation	2.352090225
Coefficient of variation (CV)	0.5930329688
Kurtosis	0.3664876888
Mean	3.966204831
Median Absolute Deviation (MAD)	1
Skewness	0.7310573319
Sum	42367
Variance	5.532328428
Monotocity	Not monotonic

Histogram with fixed size bins (bins=12)

Value	Count	Frequency (%)
4	3849	36.0%
3	2053	19.2%
1	1751	16.4%
6	1196	11.2%
8	818	7.7%
10	479	4.5%
0	319	3.0%
2	194	1.8%
7	13	0.1%
5	6	0.1%
Other values (2)	4	< 0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	319	3.0%
1	1751	16.4%
2	194	1.8%
3	2053	19.2%
4	3849	36.0%

Value	Count	Frequency (%)
11	3	< 0.1%
10	479	4.5%
9	1	< 0.1%
8	818	7.7%
7	13	0.1%

Source
Categorical

HIGH CORRELATION

Distinct	5
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	83.6 KiB

2	4536
3	2871
0	2197
4	697
1	381

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	10682
Distinct characters	5
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	3
3rd row	2
4th row	3
5th row	0

Value	Count	Frequency (%)
2	4536	42.5%
3	2871	26.9%
0	2197	20.6%
4	697	6.5%
1	381	3.6%

Histogram of lengths of the category

Value	Count	Frequency (%)
2	4536	42.5%
3	2871	26.9%
0	2197	20.6%
4	697	6.5%
1	381	3.6%

Most occurring characters

Value	Count	Frequency (%)
2	4536	42.5%
3	2871	26.9%
0	2197	20.6%
4	697	6.5%
1	381	3.6%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	10682	100.0%

Most frequent character per category

Value	Count	Frequency (%)
2	4536	42.5%
3	2871	26.9%
0	2197	20.6%
4	697	6.5%
1	381	3.6%

Most occurring scripts

Value	Count	Frequency (%)
Common	10682	100.0%

Most frequent character per script

Value	Count	Frequency (%)
2	4536	42.5%
3	2871	26.9%
0	2197	20.6%
4	697	6.5%
1	381	3.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10682	100.0%

Most frequent character per block

Value	Count	Frequency (%)
2	4536	42.5%
3	2871	26.9%
0	2197	20.6%
4	697	6.5%
1	381	3.6%

Destination
Real number (ℝ_≥0)

ZEROS

Distinct	6
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	1.436154278
Minimum	0
Maximum	5
Zeros	2871
Zeros (%)	26.9%
Memory size	83.6 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	1
Q3	2
95-th percentile	5
Maximum	5
Range	5
Interquartile range (IQR)	2

Descriptive statistics

Standard deviation	1.47484469
Coefficient of variation (CV)	1.026940289
Kurtosis	0.6319566897
Mean	1.436154278
Median Absolute Deviation (MAD)	1
Skewness	1.244045862
Sum	15341
Variance	2.175166859
Monotocity	Not monotonic

Histogram with fixed size bins (bins=6)

Value	Count	Frequency (%)
1	4536	42.5%
0	2871	26.9%
2	1265	11.8%
5	932	8.7%
3	697	6.5%
4	381	3.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	2871	26.9%
1	4536	42.5%
2	1265	11.8%
3	697	6.5%
4	381	3.6%

Value	Count	Frequency (%)
5	932	8.7%
4	381	3.6%
3	697	6.5%
2	1265	11.8%
1	4536	42.5%

Duration
Real number (ℝ_≥0)

Distinct	368
Distinct (%)	3.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	643.0205018
Minimum	5
Maximum	2860
Zeros	0
Zeros (%)	0.0%
Memory size	83.6 KiB

Quantile statistics

Minimum	5
5-th percentile	90
Q1	170
median	520
Q3	930
95-th percentile	1615
Maximum	2860
Range	2855
Interquartile range (IQR)	760

Descriptive statistics

Standard deviation	507.8301335
Coefficient of variation (CV)	0.7897572971
Kurtosis	-0.1663341759
Mean	643.0205018
Median Absolute Deviation (MAD)	350
Skewness	0.8614112576
Sum	6868745
Variance	257891.4445
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
170	550	5.1%
90	386	3.6%
165	337	3.2%
175	337	3.2%
155	329	3.1%
180	261	2.4%
140	238	2.2%
150	220	2.1%
160	158	1.5%
85	135	1.3%
Other values (358)	7731	72.4%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
5	1	< 0.1%
75	24	0.2%
80	61	0.6%
85	135	1.3%
90	386	3.6%

Value	Count	Frequency (%)
2860	1	< 0.1%
2820	1	< 0.1%
2565	1	< 0.1%
2525	1	< 0.1%
2480	1	< 0.1%

Total_Stops
Categorical

HIGH CORRELATION

Distinct	5
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	83.6 KiB

0	5625
4	3491
1	1520
2	45
3	1

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	10682
Distinct characters	5
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	< 0.1%

Sample

1st row	4
2nd row	1
3rd row	1
4th row	0
5th row	0

Value	Count	Frequency (%)
0	5625	52.7%
4	3491	32.7%
1	1520	14.2%
2	45	0.4%
3	1	< 0.1%

Histogram of lengths of the category

Value	Count	Frequency (%)
0	5625	52.7%
4	3491	32.7%
1	1520	14.2%
2	45	0.4%
3	1	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
0	5625	52.7%
4	3491	32.7%
1	1520	14.2%
2	45	0.4%
3	1	< 0.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	10682	100.0%

Most frequent character per category

Value	Count	Frequency (%)
0	5625	52.7%
4	3491	32.7%
1	1520	14.2%
2	45	0.4%
3	1	< 0.1%

Most occurring scripts

Value	Count	Frequency (%)
Common	10682	100.0%

Most frequent character per script

Value	Count	Frequency (%)
0	5625	52.7%
4	3491	32.7%
1	1520	14.2%
2	45	0.4%
3	1	< 0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10682	100.0%

Most frequent character per block

Value	Count	Frequency (%)
0	5625	52.7%
4	3491	32.7%
1	1520	14.2%
2	45	0.4%
3	1	< 0.1%

Additional_Info
Real number (ℝ_≥0)

Distinct	10
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	7.392997566
Minimum	0
Maximum	9
Zeros	19
Zeros (%)	0.2%
Memory size	83.6 KiB

Quantile statistics

Minimum	0
5-th percentile	5
Q1	8
median	8
Q3	8
95-th percentile	8
Maximum	9
Range	9
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	1.214253744
Coefficient of variation (CV)	0.1642437635
Kurtosis	2.508230984
Mean	7.392997566
Median Absolute Deviation (MAD)	0
Skewness	-1.779688529
Sum	78972
Variance	1.474412154
Monotocity	Not monotonic

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
8	8344	78.1%
5	1982	18.6%
7	320	3.0%
0	19	0.2%
4	7	0.1%
3	4	< 0.1%
6	3	< 0.1%
2	1	< 0.1%
9	1	< 0.1%
1	1	< 0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	19	0.2%
1	1	< 0.1%
2	1	< 0.1%
3	4	< 0.1%
4	7	0.1%

Value	Count	Frequency (%)
9	1	< 0.1%
8	8344	78.1%
7	320	3.0%
6	3	< 0.1%
5	1982	18.6%

year_of_Journey
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct	1
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	83.6 KiB

2019	10682

Length

Max length	4
Median length	4
Mean length	4
Min length	4

Characters and Unicode

Total characters	42728
Distinct characters	4
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	2019
2nd row	2019
3rd row	2019
4th row	2019
5th row	2019

Value	Count	Frequency (%)
2019	10682	100.0%

Histogram of lengths of the category

Value	Count	Frequency (%)
2019	10682	100.0%

Most occurring characters

Value	Count	Frequency (%)
2	10682	25.0%
0	10682	25.0%
1	10682	25.0%
9	10682	25.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	42728	100.0%

Most frequent character per category

Value	Count	Frequency (%)
2	10682	25.0%
0	10682	25.0%
1	10682	25.0%
9	10682	25.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	42728	100.0%

Most frequent character per script

Value	Count	Frequency (%)
2	10682	25.0%
0	10682	25.0%
1	10682	25.0%
9	10682	25.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	42728	100.0%

Most frequent character per block

Value	Count	Frequency (%)
2	10682	25.0%
0	10682	25.0%
1	10682	25.0%
9	10682	25.0%

month_of_Journey
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	4
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	83.6 KiB

5	3465
6	3414
3	2724
4	1079

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	10682
Distinct characters	4
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	3
2nd row	5
3rd row	6
4th row	5
5th row	3

Value	Count	Frequency (%)
5	3465	32.4%
6	3414	32.0%
3	2724	25.5%
4	1079	10.1%

Histogram of lengths of the category

Value	Count	Frequency (%)
5	3465	32.4%
6	3414	32.0%
3	2724	25.5%
4	1079	10.1%

Most occurring characters

Value	Count	Frequency (%)
5	3465	32.4%
6	3414	32.0%
3	2724	25.5%
4	1079	10.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	10682	100.0%

Most frequent character per category

Value	Count	Frequency (%)
5	3465	32.4%
6	3414	32.0%
3	2724	25.5%
4	1079	10.1%

Most occurring scripts

Value	Count	Frequency (%)
Common	10682	100.0%

Most frequent character per script

Value	Count	Frequency (%)
5	3465	32.4%
6	3414	32.0%
3	2724	25.5%
4	1079	10.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10682	100.0%

Most frequent character per block

Value	Count	Frequency (%)
5	3465	32.4%
6	3414	32.0%
3	2724	25.5%
4	1079	10.1%

week_of_Journey
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	18
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	18.41368658
Minimum	9
Maximum	26
Zeros	0
Zeros (%)	0.0%
Memory size	83.6 KiB

Quantile statistics

Minimum	9
5-th percentile	10
Q1	13
median	20
Q3	23
95-th percentile	26
Maximum	26
Range	17
Interquartile range (IQR)	10

Descriptive statistics

Standard deviation	5.227373156
Coefficient of variation (CV)	0.2838852032
Kurtosis	-1.147488123
Mean	18.41368658
Median Absolute Deviation (MAD)	4
Skewness	-0.4050218433
Sum	196695
Variance	27.32543011
Monotocity	Not monotonic

Histogram with fixed size bins (bins=18)

Value	Count	Frequency (%)
23	1331	12.5%
19	1024	9.6%
20	909	8.5%
12	902	8.4%
24	821	7.7%
21	783	7.3%
22	724	6.8%
26	706	6.6%
10	705	6.6%
9	514	4.8%
Other values (8)	2263	21.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
9	514	4.8%
10	705	6.6%
11	304	2.8%
12	902	8.4%
13	299	2.8%

Value	Count	Frequency (%)
26	706	6.6%
25	214	2.0%
24	821	7.7%
23	1331	12.5%
22	724	6.8%

day_of_Journey
Real number (ℝ_≥0)

Distinct	10
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	13.5090807
Minimum	1
Maximum	27
Zeros	0
Zeros (%)	0.0%
Memory size	83.6 KiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	6
median	12
Q3	21
95-th percentile	27
Maximum	27
Range	26
Interquartile range (IQR)	15

Descriptive statistics

Standard deviation	8.479363137
Coefficient of variation (CV)	0.6276787686
Kurtosis	-1.272847284
Mean	13.5090807
Median Absolute Deviation (MAD)	6
Skewness	0.1181743134
Sum	144304
Variance	71.89959921
Monotocity	Not monotonic

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
9	1406	13.2%
6	1287	12.0%
27	1130	10.6%
21	1111	10.4%
1	1075	10.1%
24	1052	9.8%
15	984	9.2%
12	957	9.0%
3	848	7.9%
18	832	7.8%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	1075	10.1%
3	848	7.9%
6	1287	12.0%
9	1406	13.2%
12	957	9.0%

Value	Count	Frequency (%)
27	1130	10.6%
24	1052	9.8%
21	1111	10.4%
18	832	7.8%
15	984	9.2%

hour_of_Journey
Real number (ℝ_≥0)

Distinct	24
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	12.49101292
Minimum	0
Maximum	23
Zeros	40
Zeros (%)	0.4%
Memory size	83.6 KiB

Quantile statistics

Minimum	0
5-th percentile	5
Q1	8
median	11
Q3	18
95-th percentile	22
Maximum	23
Range	23
Interquartile range (IQR)	10

Descriptive statistics

Standard deviation	5.748820008
Coefficient of variation (CV)	0.4602364953
Kurtosis	-1.194929286
Mean	12.49101292
Median Absolute Deviation (MAD)	5
Skewness	0.1129237509
Sum	133429
Variance	33.04893149
Monotocity	Not monotonic

Histogram with fixed size bins (bins=24)

Value	Count	Frequency (%)
9	915	8.6%
7	867	8.1%
8	697	6.5%
17	695	6.5%
6	687	6.4%
20	651	6.1%
5	629	5.9%
11	580	5.4%
19	567	5.3%
10	536	5.0%
Other values (14)	3858	36.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	40	0.4%
1	37	0.3%
2	194	1.8%
3	24	0.2%
4	170	1.6%

Value	Count	Frequency (%)
23	161	1.5%
22	387	3.6%
21	492	4.6%
20	651	6.1%
19	567	5.3%

minute_of_Journey
Real number (ℝ_≥0)

ZEROS

Distinct	12
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	24.40928665
Minimum	0
Maximum	55
Zeros	2062
Zeros (%)	19.3%
Memory size	83.6 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	5
median	25
Q3	40
95-th percentile	55
Maximum	55
Range	55
Interquartile range (IQR)	35

Descriptive statistics

Standard deviation	18.76780146
Coefficient of variation (CV)	0.768879555
Kurtosis	-1.292665532
Mean	24.40928665
Median Absolute Deviation (MAD)	20
Skewness	0.1672339983
Sum	260740
Variance	352.2303716
Monotocity	Not monotonic

Histogram with fixed size bins (bins=12)

Value	Count	Frequency (%)
0	2062	19.3%
30	1215	11.4%
55	1058	9.9%
10	890	8.3%
45	875	8.2%
5	773	7.2%
15	692	6.5%
25	691	6.5%
20	666	6.2%
35	665	6.2%
Other values (2)	1095	10.3%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	2062	19.3%
5	773	7.2%
10	890	8.3%
15	692	6.5%
20	666	6.2%

Value	Count	Frequency (%)
55	1058	9.9%
50	591	5.5%
45	875	8.2%
40	504	4.7%
35	665	6.2%

Price
Real number (ℝ_≥0)

Distinct	1870
Distinct (%)	17.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	9087.214567
Minimum	1759
Maximum	79512
Zeros	0
Zeros (%)	0.0%
Memory size	83.6 KiB

Quantile statistics

Minimum	1759
5-th percentile	3543
Q1	5277
median	8372
Q3	12373
95-th percentile	15764
Maximum	79512
Range	77753
Interquartile range (IQR)	7096

Descriptive statistics

Standard deviation	4611.54881
Coefficient of variation (CV)	0.5074766064
Kurtosis	13.30193677
Mean	9087.214567
Median Absolute Deviation (MAD)	3382
Skewness	1.812404555
Sum	97069626
Variance	21266382.43
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
10262	258	2.4%
10844	212	2.0%
7229	162	1.5%
4804	160	1.5%
4823	131	1.2%
14714	109	1.0%
3943	104	1.0%
15129	93	0.9%
3841	91	0.9%
12898	86	0.8%
Other values (1860)	9276	86.8%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1759	4	< 0.1%
1840	1	< 0.1%
1965	36	0.3%
2017	35	0.3%
2050	10	0.1%

Value	Count	Frequency (%)
79512	1	< 0.1%
62427	1	< 0.1%
57209	1	< 0.1%
54826	3	< 0.1%
52285	1	< 0.1%

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Count
Matrix

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

First rows

	df_index	Airline	Source	Destination	Duration	Total_Stops	Additional_Info	year_of_Journey	month_of_Journey	week_of_Journey	day_of_Journey	hour_of_Journey	minute_of_Journey	Price
0	0	3	0	5	170	4	8	2019	3	12	24	22	20	3897
1	1	1	3	0	445	1	8	2019	5	18	1	5	50	7662
2	2	4	2	1	1140	1	8	2019	6	23	9	9	25	13882
3	3	3	3	0	325	0	8	2019	5	19	12	18	5	6218
4	4	3	0	5	285	0	8	2019	3	9	1	16	50	13302
5	5	8	3	0	145	4	8	2019	6	26	24	9	0	3873
6	6	4	0	5	930	0	5	2019	3	11	12	18	55	11087
7	7	4	0	5	1265	0	8	2019	3	9	1	8	0	22270
8	8	4	0	5	1530	0	5	2019	3	11	12	8	55	11087
9	9	6	2	1	470	0	8	2019	5	22	27	11	25	8625

Last rows

	df_index	Airline	Source	Destination	Duration	Total_Stops	Additional_Info	year_of_Journey	month_of_Journey	week_of_Journey	day_of_Journey	hour_of_Journey	minute_of_Journey	Price
10672	10673	4	2	1	900	1	8	2019	5	22	27	13	25	16704
10673	10674	4	0	5	1485	0	5	2019	3	11	12	20	35	11087
10674	10675	1	4	3	80	4	8	2019	6	23	9	6	20	3100
10675	10676	6	2	1	520	0	8	2019	5	18	1	10	20	9794
10676	10677	8	0	2	160	4	7	2019	5	21	21	5	55	3257
10677	10678	0	3	0	150	4	8	2019	4	15	9	19	55	4107
10678	10679	1	3	0	155	4	8	2019	4	17	27	20	45	4145
10679	10680	4	0	2	180	4	8	2019	4	17	27	8	20	7229
10680	10681	10	0	5	160	4	8	2019	3	9	1	11	30	12648
10681	10682	1	2	1	500	1	8	2019	5	19	9	10	55	11753

Overview

Variables

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Interactions

Correlations

Pearson's r

Spearman's ρ

Kendall's τ

Phik (φk)

Cramér's V (φc)

Missing values

Sample

First rows

Last rows